Building Jetflow: a framework for flexible, performant data pipelines at Cloudflare

The Cloudflare Business Intelligence team manages a petabyte-scale data lake and ingests thousands of tables every day from many different sources. These include internal databases such as Postgres and ClickHouse, as well as external SaaS applications such as Salesforce. These tasks are often complex and tables may have hundreds of millions or billions of rows of new data each day. They are also business-critical for product decisions, growth plannings, and internal monitoring. In total, about 141 billion rows are ingested every day.

As Cloudflare has grown, the data has become ever larger and more complex. Our existing Extract Load Transform (ELT) solution could no longer meet our technical and business requirements. After evaluating other common ELT solutions, we concluded that their performance generally did not surpass our current system, either.

It became clear that we needed to build our own framework to cope with our unique requirements — and so Jetflow was born. 

Over 100x efficiency improvement in GB-s:

• Our longest running job with 19 billion rows was taking 48 hours using 300 GB of memory, and now completes in 5.5 hours using 4 GB of memory

• We estimate that ingestion of Continue reading